Research Articles

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Browsing Research Articles by Author "Ahmad, W."

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    Mesoporous silica supported orderly-spaced gold nanoparticles SERS-based sensor for pesticides detection in food
    (Elsevier Ltd, 2020) Xu, Y.; Kutsanedzie, F. Y. H.; Hassan, M.; Zhu, J.; Ahmad, W.; Li, H.; Chen, Q.
    In this study, a novel sensor fabricated with compactly arranged gold nanoparticles (AuNPs) templated from mesoporous silica film (MSF) via air-water interface has been confirmed as a promising surface-enhanced Raman scattering (SERS) substrate for detecting trace levels of 2,4-dichlorophenoxyacetic acid (2,4-D), pymetrozine and thiamethoxam. The densely arranged AuNPs@MSF had an average AuNPs size of 5.15 nm with small nanogaps (<2nm) between AuNPs, and exhibited a high SERS performance. SERS spectra of pesticides were collected after their adsorption on the AuNPs@MSF. The results showed that the concentration of 2,4-D, pymetrozine and thiamethoxam gave a good linear relationship with SERS intensity. Moreover, the designed SERS-based sensor (AuNPs@MSF) was stable for 3 months with ca. 3% relative standard deviation (RSD) and was applied successfully for the analysis of 2,4-D extraction from both environmental and food samples. The proposed SERS-based sensor was further validated by HPLC and showed satisfactory result (p > 0.05).
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    An overview on the applications of typical non-linear algorithms coupled with NIR spectroscopy in food analysis
    (Food Engineering Reviews, 2020) Zareef, M.; Chen, Q.; Hassan, M. M.; Arslan, M.; Hashim, M. M.; Ahmad, W.; Kutsanedzie, F. Y.; Agyekum, A. A.
    Near-infrared (NIR) spectroscopy as a low-cost technique with its non-destructive fast nature, precision, control, accuracy, repeatability, and reproducibility has been extensively employed in most industries for food quality measurements. Its coupling to different modeling techniques has been identified as a way of improving the accuracy and robustness of non-destructive measurement of foodstuffs. This review provides an overview of the application of non-linear algorithms in food quality and safety specific to NIR spectroscopy. The review also provides in-depth knowledge about the principle of NIR spectroscopy along with different non-linear models such as artificial neural network (ANN), AdaBoost, local algorithm (LA), support vector machine (SVM), and extreme learning machine (ELM). Moreover, non-linear algorithms coupled with NIR spectroscopy for ensuring food quality and their future perspective has been discussed.